Investigating the Implementation of the Artificial Bee Colony Using the ArcGIS Environment: Dubai Drone Box Platform Case Study

Deploying drones in different real-life world applications can enhance user experience and maximize system benefits. The “Drone Box” project launched by Dubai aims to reduce the response time to traffic accidents and crimes; therefore, identifying optimal locations for these boxes is crucial. We propose a hybrid AI-GIS-based system to localize the drone boxes across Dubai strategically. We formulate the problem as a P-center Facility Location Problem (FLP) and construct a suitable objective function accordingly. Since the dataset needed was not provided, we designed a random dataset generator for testing purposes. We selected the Genetic Algorithm (GA) for benchmarking and investigated the performance of Artificial Bee Colony (ABC) algorithms due to their relevance to FLP. Geographic Information System (GIS) functions were employed to construct the random dataset generator and implement the ABC algorithm, utilizing the additional functionalities GIS offers for handling geographical data. After testing both algorithms, we deduced that the GA without GIS function integration consistently achieved a higher fitness value in a remarkable time, demonstrating its superiority over the ABC Algorithm.